"""
this file is to save the recorded datas
"""
import numpy as np

# interpolation nombre de points faible
data = np.array([
[0.00, 5186, -4240, 5132, -4315, 3109, 2546, 3080, 2588],
[0.31, 5928, -3135, 4425, -5227, 2987, 2835, 3029, 2607],
[0.61, 6803, -2046, 3800, -6335, 2838, 3139, 2931, 2584],
[0.92, 7698, -959, 3186, -7470, 2684, 3446, 2826, 2555],
[1.23, 8496, 134, 2517, -8464, 2550, 3741, 2754, 2556],
[1.53, 9080, 1242, 1728, -9146, 2461, 4009, 2757, 2622],
[1.82, 9327, 2284, 839, -9350, 2439, 4220, 2859, 2772],
[2.09, 9220, 3322, -233, -9035, 2488, 4384, 3083, 3028],
[2.36, 8815, 4510, -1727, -8174, 2589, 4543, 3498, 3442],
[2.63, 8167, 5810, -3549, -6877, 2733, 4695, 4063, 3982],
[2.90, 7314, 7136, -5507, -5270, 2919, 4825, 4706, 4590],
[3.18, 6286, 8404, -7422, -3472, 3147, 4916, 5359, 5213],
[3.45, 5128, 9517, -9088, -1621, 3412, 4951, 5947, 5791],
[3.72, 3868, 10395, -10327, 168, 3717, 4914, 6403, 6270],
[3.99, 2550, 10945, -10942, 1759, 4056, 4788, 6652, 6591],
[4.27, 960, 11188, -10853, 3330, 4503, 4486, 6662, 6749],
[4.54, -1040, 11215, -10200, 5089, 5092, 3979, 6482, 6796],
[4.81, -3240, 11037, -9130, 6889, 5751, 3365, 6172, 6755],
[5.08, -5458, 10662, -7781, 8613, 6414, 2733, 5787, 6650],
[5.36, -7485, 10100, -6298, 10119, 7008, 2178, 5385, 6506],
[5.63, -9119, 9365, -4830, 11271, 7462, 1796, 5027, 6347],
[5.90, -10178, 8453, -3503, 11948, 7709, 1676, 4766, 6195],
[6.18, -10465, 7283, -2351, 11995, 7682, 1938, 4645, 6064],
[6.45, -10043, 5595, -1051, 11396, 7403, 2627, 4620, 5918],
[6.73, -9105, 3582, 318, 10327, 6940, 3591, 4655, 5756],
[7.00, -7822, 1420, 1676, 8942, 6353, 4696, 4721, 5575],
[7.28, -6393, -661, 2907, 7429, 5713, 5778, 4788, 5377],
[7.55, -5007, -2456, 3909, 5963, 5088, 6685, 4827, 5164],
[7.83, -3824, -3789, 4598, 4690, 4533, 7283, 4806, 4932],
[8.10, -3017, -4447, 4863, 3774, 4109, 7423, 4700, 4681],
[8.38, -2410, -4497, 4687, 3054, 3756, 7173, 4525, 4405],
[8.65, -1903, -4095, 4165, 2436, 3436, 6641, 4300, 4105],
[8.93, -1465, -3369, 3395, 1889, 3139, 5904, 4039, 3786],
[9.20, -1069, -2447, 2472, 1384, 2856, 5043, 3756, 3456],
[9.48, -688, -1465, 1506, 894, 2578, 4147, 3467, 3124],
[9.75, -293, -555, 595, 391, 2296, 3296, 3187, 2796],
[10.03, 101, 101, -101, -101, 2029, 2631, 2952, 2509]])


X1 = np.array([5184.0,9293.0,2516.0,-10372.0,-3280.0,101.0])
X2 = np.array([-4244.0,2981.0,10955.0,8094.0,-4284.0,101.0])
X3 = np.array([5135.0,145.0,-10948.0,-3100.0,4819.0,-101.0])
X4 = np.array([-4313.0,-9198.0,1797.0,12045.0,4080.0,-101.0])

V1 = np.array([3110.0,2465.0,4066.0,7733.0,4255.0,2029.0])
V2 = np.array([2546.0,4335.0,4784.0,1717.0,7427.0,2631.0])
V3 = np.array([3081.0,2994.0,6656.0,4709.0,4751.0,2952.0])
V4 = np.array([2588.0,2931.0,6597.0,6149.0,4779.0,2509.0])

#interpolation N = 50 points catmull spline
data = np.array([
[0.00, -447, -1553, 1562, 539, 2231, 7691, 7736, 2669],
[0.28, -88, -3195, 3198, 467, 1491, 5880, 5847, 516],
[0.55, 1094, -4331, 4351, -393, 4726, 3970, 4081, 3536],
[0.82, 2821, -4870, 5092, -1885, 6647, 1714, 2576, 5830],
[1.10, 4870, -4727, 5489, -3847, 7743, 607, 1325, 7496],
[1.37, 7038, -3887, 5585, -6095, 8123, 3462, 111, 8497],
[1.65, 9182, -2407, 5384, -8477, 7843, 5735, 890, 8789],
[1.92, 11086, -477, 4849, -10715, 6951, 7372, 2164, 8224],
[2.20, 12618, 1760, 3888, -12553, 5436, 8371, 3780, 6509],
[2.47, 13597, 4128, 2384, -13547, 3347, 8836, 5864, 3170],
[2.75, 13894, 6577, 155, -13235, 832, 9008, 8568, 1538],
[3.03, 13456, 8987, -2788, -11431, 1908, 8909, 11238, 7372],
[3.30, 12412, 11217, -6171, -8552, 4148, 8158, 12706, 11111],
[3.58, 10822, 13054, -9610, -5149, 6161, 6570, 12683, 12761],
[3.85, 8641, 14226, -12558, -1685, 8397, 3970, 10561, 12797],
[4.13, 5736, 14424, -14117, 1525, 11191, 920, 4799, 11811],
[4.40, 1926, 13413, -13309, 4415, 14446, 4205, 3608, 10490],
[4.68, -2505, 11417, -10229, 7041, 16529, 7737, 12265, 9572],
[4.95, -6960, 8859, -5963, 9425, 16522, 9757, 16308, 8765],
[5.23, -10805, 5942, -1283, 11497, 13611, 10860, 17241, 7413],
[5.51, -12937, 2816, 3116, 12938, 6808, 11605, 15969, 4937],
[5.78, -12568, -546, 6791, 13379, 1563, 12510, 13150, 1447],
[6.06, -10180, -4139, 9657, 12774, 9485, 13320, 10198, 2536],
[6.34, -6868, -7766, 11853, 11398, 12442, 13274, 7745, 5381],
[6.62, -3376, -11035, 13421, 9504, 12846, 11775, 5479, 7180],
[6.89, -170, -13426, 14335, 7297, 11576, 8232, 3026, 8239],
[7.17, 2377, -14348, 14459, 4933, 9020, 2789, 383, 8764],
[7.45, 4126, -13686, 13728, 2506, 6087, 2707, 3033, 8960],
[7.72, 5237, -11914, 12290, 102, 3825, 6936, 5600, 8812],
[8.00, 5879, -9540, 10329, -2121, 2147, 8941, 7418, 8042],
[8.28, 6163, -6935, 8048, -3939, 863, 9638, 8514, 6446],
[8.56, 6158, -4373, 5643, -5139, 193, 9364, 8876, 4078],
[8.83, 5871, -2081, 3319, -5573, 1198, 8277, 8489, 1257],
[9.11, 5252, -259, 1278, -5227, 2452, 6402, 7293, 1490],
[9.39, 4225, 864, -202, -4213, 4028, 3813, 5186, 4056],
[9.66, 2682, 1126, -861, -2646, 5962, 1091, 1719, 6042],
[9.94, 546, 305, -276, -538, 8059, 3320, 2451, 7949],
[10.22, 28, 28, -28, -28, 8520, 4320, 3770, 8385]])


X1 = np.array([-449.0,-273.0,398.0,1447.0,2768.0,4270.0,5870.0,7494.0,9069.0,10528.0,11803.0,12827.0,13538.0,13879.0,13807.0,13355.0,12579.0,11504.0,10122.0,8394.0,6255.0,3630.0,568.0,-2749.0,-6094.0,-9173.0,-11605.0,-12948.0,-12892.0,-11587.0,-9498.0,-7024.0,-4440.0,-1944.0,303.0,2164.0,3577.0,4609.0,5331.0,5806.0,6082.0,6191.0,6150.0,5956.0,5592.0,5025.0,4217.0,3128.0,1732.0,28.0])
X2 = np.array([-1541.0,-2811.0,-3811.0,-4509.0,-4865.0,-4841.0,-4423.0,-3628.0,-2503.0,-1116.0,460.0,2157.0,3919.0,5711.0,7515.0,9286.0,10946.0,12406.0,13560.0,14292.0,14473.0,13984.0,12868.0,11292.0,9404.0,7318.0,5102.0,2779.0,326.0,-2267.0,-4948.0,-7609.0,-10095.0,-12204.0,-13691.0,-14332.0,-14082.0,-13122.0,-11673.0,-9928.0,-8032.0,-6103.0,-4238.0,-2524.0,-1048.0,110.0,869.0,1153.0,892.0,28.0])
X3 = np.array([1550.0,2818.0,3811.0,4554.0,5077.0,5409.0,5570.0,5569.0,5404.0,5056.0,4494.0,3674.0,2542.0,1035.0,-902.0,-3203.0,-5722.0,-8300.0,-10743.0,-12781.0,-14016.0,-13981.0,-12540.0,-10023.0,-6868.0,-3443.0,-26.0,3163.0,5948.0,8274.0,10198.0,11768.0,13004.0,13899.0,14414.0,14486.0,14083.0,13262.0,12094.0,10657.0,9028.0,7286.0,5511.0,3784.0,2192.0,825.0,-209.0,-792.0,-782.0,-28.0])
X4 = np.array([539.0,569.0,141.0,-682.0,-1837.0,-3255.0,-4864.0,-6588.0,-8347.0,-10048.0,-11578.0,-12792.0,-13508.0,-13528.0,-12709.0,-11114.0,-8964.0,-6496.0,-3909.0,-1361.0,1041.0,3242.0,5271.0,7177.0,8968.0,10597.0,11970.0,12950.0,13376.0,13200.0,12528.0,11472.0,10129.0,8587.0,6915.0,5169.0,3387.0,1594.0,-158.0,-1801.0,-3244.0,-4398.0,-5184.0,-5549.0,-5485.0,-5019.0,-4205.0,-3092.0,-1705.0,-28.0])

V1 = np.array([2245.0,880.0,3355.0,5245.0,6605.0,7510.0,8000.0,8120.0,7875.0,7295.0,6375.0,5120.0,3555.0,1705.0,360.0,2260.0,3880.0,5375.0,6910.0,8640.0,10695.0,13125.0,15310.0,16585.0,16725.0,15395.0,12160.0,6715.0,280.0,6525.0,10445.0,12370.0,12920.0,12480.0,11235.0,9305.0,7065.0,5160.0,3610.0,2375.0,1380.0,545.0,205.0,970.0,1820.0,2835.0,4040.0,5445.0,6980.0,8520.0])
V2 = np.array([7705.0,6350.0,5000.0,3490.0,1780.0,120.0,2090.0,3975.0,5625.0,6935.0,7880.0,8485.0,8810.0,8960.0,9020.0,8855.0,8300.0,7300.0,5770.0,3660.0,905.0,2445.0,5580.0,7880.0,9440.0,10430.0,11080.0,11615.0,12265.0,12965.0,13405.0,13305.0,12430.0,10545.0,7435.0,3205.0,1250.0,4800.0,7245.0,8725.0,9480.0,9645.0,9325.0,8570.0,7380.0,5790.0,3795.0,1420.0,1305.0,4320.0])
V3 = np.array([7750.0,6340.0,4965.0,3715.0,2615.0,1660.0,805.0,5.0,825.0,1740.0,2810.0,4100.0,5660.0,7535.0,9685.0,11505.0,12595.0,12890.0,12215.0,10190.0,6175.0,175.0,7205.0,12585.0,15775.0,17125.0,17085.0,15945.0,13925.0,11630.0,9620.0,7850.0,6180.0,4475.0,2575.0,360.0,2015.0,4105.0,5840.0,7185.0,8145.0,8710.0,8875.0,8635.0,7960.0,6835.0,5170.0,2915.0,50.0,3770.0])
V4 = np.array([2695.0,150.0,2140.0,4115.0,5775.0,7090.0,8045.0,8620.0,8795.0,8505.0,7650.0,6070.0,3580.0,100.0,4095.0,7975.0,10750.0,12340.0,12935.0,12740.0,12010.0,11005.0,10145.0,9530.0,8955.0,8145.0,6865.0,4900.0,2130.0,880.0,3360.0,5280.0,6715.0,7710.0,8360.0,8730.0,8910.0,8965.0,8760.0,8215.0,7215.0,5770.0,3930.0,1825.0,320.0,2330.0,4070.0,5565.0,6935.0,8385.0])

# interpolation 25 points linéaire
data = np.array([
[0.00, -214, -2616, 2621, 470, 566, 6508, 6522, 1196],
[0.27, 722, -3596, 3619, -217, 2549, 4717, 4765, 2145],
[0.55, 1958, -4201, 4348, -1269, 4321, 2802, 3136, 3535],
[0.82, 3512, -4380, 4770, -2712, 5839, 773, 1668, 5401],
[1.10, 5287, -3732, 4746, -4567, 6461, 1894, 701, 6516],
[1.37, 7043, -2719, 4517, -6477, 6699, 3422, 630, 7197],
[1.64, 8734, -1302, 4054, -8401, 6493, 5258, 1679, 7355],
[1.91, 10085, 537, 3154, -9953, 5626, 6484, 2865, 6439],
[2.19, 11165, 2521, 1950, -11078, 4414, 7410, 4236, 4784],
[2.46, 11835, 4618, 358, -11547, 2784, 7927, 5850, 2155],
[2.74, 11772, 6736, -1908, -10642, 1507, 8053, 7763, 3206],
[3.01, 11327, 8758, -4414, -9101, 1348, 7826, 9370, 5324],
[3.28, 10365, 10575, -7168, -6747, 3295, 7028, 10270, 8371],
[3.56, 8769, 11728, -9524, -4095, 5246, 5255, 9486, 9703],
[3.83, 6741, 12346, -11279, -1425, 7356, 3349, 7377, 10255],
[4.10, 4000, 12019, -11789, 1132, 9851, 1634, 2950, 9821],
[4.38, 591, 10615, -10275, 3478, 12139, 3941, 5041, 9242],
[4.65, -3029, 8700, -7767, 5734, 13792, 7053, 9048, 8640],
[4.92, -6578, 6247, -4111, 7822, 13595, 8851, 12870, 8117],
[5.20, -9066, 3613, -346, 9512, 10824, 9767, 14155, 6933],
[5.47, -10607, 905, 3264, 10789, 7039, 10268, 13952, 5175],
[5.75, -10106, -1869, 6180, 11098, 3165, 10509, 11818, 2155],
[6.02, -8444, -4651, 8435, 10593, 4802, 10555, 9421, 2162],
[6.29, -6176, -7333, 10224, 9585, 8534, 10305, 6980, 3675],
[6.57, -3554, -9577, 11307, 7948, 9589, 9000, 4875, 5547],
[6.84, -1170, -11006, 11839, 6087, 9373, 6493, 2739, 6781],
[7.12, 988, -11787, 11951, 4095, 8324, 3585, 985, 7565],
[7.39, 2472, -11168, 11246, 2063, 6412, 2705, 2193, 7681],
[7.66, 3590, -9941, 10130, 128, 4726, 3872, 3706, 7482],
[7.94, 4426, -8277, 8709, -1704, 3224, 6288, 5365, 7014],
[8.21, 4845, -6272, 6948, -3105, 2101, 7228, 6300, 5861],
[8.49, 5043, -4318, 5148, -4091, 1041, 7503, 6799, 4296],
[8.76, 5046, -2428, 3333, -4711, 105, 7207, 6915, 2431],
[9.03, 4595, -1013, 1786, -4473, 1187, 5979, 6219, 1405],
[9.31, 3824, -20, 584, -3810, 2508, 4311, 5003, 1964],
[9.58, 2762, 564, -278, -2755, 4041, 2247, 3309, 4010],
[9.86, 947, 50, 47, -943, 5915, 2066, 1971, 5897],
[10.13, -6, -223, 223, 8, 6898, 1980, 1272, 6885]])


X1 = np.array([-221.0,1219.0,3582.0,6298.0,8888.0,10906.0,11929.0,11651.0,10193.0,7542.0,3373.0,-2163.0,-7579.0,-10709.0,-9944.0,-6598.0,-2610.0,811.0,3069.0,4394.0,5033.0,5061.0,4375.0,2753.0,-6.0])
X2 = np.array([-2609.0,-4116.0,-4389.0,-3344.0,-1174.0,1710.0,4910.0,8148.0,10902.0,12442.0,11945.0,9299.0,5556.0,1468.0,-2767.0,-6973.0,-10385.0,-11861.0,-10920.0,-8434.0,-5374.0,-2475.0,-323.0,569.0,-223.0])
X3 = np.array([2614.0,4148.0,4789.0,4722.0,4012.0,2567.0,137.0,-3490.0,-7663.0,-11131.0,-11906.0,-8660.0,-3081.0,2673.0,7124.0,10051.0,11698.0,12035.0,10964.0,8847.0,6159.0,3384.0,1032.0,-286.0,223.0])
X4 = np.array([476.0,-583.0,-2777.0,-5628.0,-8576.0,-10897.0,-11613.0,-9892.0,-6325.0,-2172.0,1717.0,5224.0,8412.0,10727.0,11198.0,9848.0,7359.0,4338.0,1247.0,-1595.0,-3733.0,-4719.0,-4357.0,-2746.0,8.0])

V1 = np.array([552.0,3600.0,5908.0,6790.0,6475.0,5045.0,2558.0,695.0,3645.0,6628.0,10422.0,13840.0,13540.0,7825.0,1912.0,8365.0,9970.0,8552.0,5645.0,3312.0,1598.0,70.0,1715.0,4055.0,6898.0])
V2 = np.array([6522.0,3768.0,682.0,2612.0,5425.0,7210.0,8000.0,8095.0,6885.0,3850.0,1242.0,6615.0,9358.0,10220.0,10588.0,10515.0,8530.0,3690.0,2352.0,6215.0,7650.0,7248.0,5380.0,2230.0,1980.0])
V3 = np.array([6535.0,3835.0,1602.0,168.0,1775.0,3612.0,6075.0,9068.0,10432.0,8670.0,1938.0,8115.0,13948.0,14385.0,11128.0,7318.0,4118.0,842.0,2678.0,5292.0,6720.0,6938.0,5880.0,3295.0,1272.0])
V4 = np.array([1190.0,2648.0,5485.0,7128.0,7370.0,5802.0,1790.0,4302.0,8918.0,10382.0,9722.0,8768.0,7970.0,5788.0,1178.0,3375.0,6222.0,7552.0,7728.0,7105.0,5345.0,2465.0,905.0,4028.0,6885.0])

#interpolation 25 point linéaire trajectoire petite taille
data = np.array([
[0.00, 204, -783, 785, -181, 511, 1955, 1959, 453],
[0.27, 470, -1021, 1030, -430, 842, 1267, 1286, 779],
[0.55, 759, -1146, 1168, -710, 1077, 628, 671, 1030],
[0.82, 1081, -1146, 1189, -1030, 1211, 30, 107, 1203],
[1.09, 1385, -963, 1035, -1347, 1176, 460, 419, 1207],
[1.37, 1653, -706, 808, -1630, 1064, 893, 780, 1119],
[1.64, 1874, -366, 498, -1866, 861, 1260, 1147, 920],
[1.92, 1965, 58, 85, -1961, 515, 1507, 1437, 544],
[2.19, 1976, 505, -360, -1965, 311, 1686, 1669, 337],
[2.46, 1881, 974, -844, -1848, 355, 1777, 1825, 431],
[2.74, 1645, 1415, -1317, -1570, 715, 1715, 1814, 848],
[3.01, 1335, 1815, -1751, -1213, 1117, 1575, 1707, 1293],
[3.28, 921, 2149, -2121, -749, 1507, 1327, 1463, 1697],
[3.55, 416, 2360, -2350, -208, 1810, 969, 1060, 1966],
[3.83, -123, 2484, -2477, 352, 2043, 584, 640, 2140],
[4.10, -690, 2457, -2429, 914, 2145, 200, 277, 2147],
[4.37, -1235, 2248, -2176, 1421, 2110, 557, 695, 2008],
[4.64, -1744, 1943, -1817, 1880, 1978, 1121, 1321, 1789],
[4.92, -2159, 1514, -1329, 2238, 1675, 1516, 1733, 1467],
[5.19, -2433, 1064, -838, 2472, 1229, 1688, 1869, 1055],
[5.46, -2603, 614, -360, 2614, 729, 1728, 1842, 621],
[5.73, -2573, 210, 36, 2576, 279, 1596, 1606, 272],
[6.01, -2425, -186, 406, 2432, 410, 1533, 1458, 411],
[6.28, -2192, -591, 773, 2211, 865, 1526, 1382, 820],
[6.55, -1851, -1042, 1176, 1900, 1173, 1663, 1492, 1079],
[6.83, -1466, -1511, 1600, 1561, 1404, 1757, 1584, 1252],
[7.10, -1054, -1978, 2026, 1204, 1570, 1794, 1637, 1357],
[7.38, -627, -2311, 2334, 830, 1605, 1432, 1316, 1401],
[7.65, -227, -2474, 2481, 456, 1555, 840, 767, 1423],
[7.92, 147, -2486, 2486, 82, 1429, 87, 60, 1422],
[8.20, 434, -2193, 2199, -253, 1200, 772, 749, 1321],
[8.47, 661, -1821, 1835, -532, 941, 1312, 1285, 1135],
[8.75, 831, -1366, 1390, -759, 649, 1716, 1679, 863],
[9.02, 852, -909, 936, -816, 273, 1732, 1712, 437],
[9.29, 781, -523, 547, -768, 254, 1568, 1572, 337],
[9.57, 603, -215, 229, -601, 651, 1199, 1234, 620],
[9.84, 191, -179, 184, -189, 1263, 493, 528, 1247],
[10.11, -61, -169, 169, 62, 1632, 65, 98, 1630]])


X1 = np.array([204.0,610.0,1097.0,1558.0,1895.0,2013.0,1868.0,1473.0,839.0,33.0,-836.0,-1654.0,-2287.0,-2609.0,-2563.0,-2230.0,-1709.0,-1082.0,-433.0,141.0,576.0,834.0,863.0,592.0,-61.0])
X2 = np.array([-783.0,-1146.0,-1147.0,-853.0,-335.0,326.0,1042.0,1705.0,2216.0,2492.0,2451.0,2037.0,1382.0,682.0,63.0,-542.0,-1230.0,-1957.0,-2464.0,-2493.0,-2049.0,-1360.0,-665.0,-195.0,-169.0])
X3 = np.array([785.0,1159.0,1191.0,942.0,469.0,-175.0,-914.0,-1629.0,-2195.0,-2491.0,-2417.0,-1924.0,-1180.0,-427.0,181.0,729.0,1344.0,2007.0,2475.0,2493.0,2058.0,1384.0,693.0,208.0,169.0])
X4 = np.array([-181.0,-561.0,-1046.0,-1528.0,-1889.0,-2010.0,-1832.0,-1368.0,-657.0,198.0,1058.0,1802.0,2349.0,2621.0,2563.0,2246.0,1771.0,1229.0,660.0,90.0,-419.0,-763.0,-846.0,-590.0,62.0])

V1 = np.array([510.0,1015.0,1218.0,1152.0,842.0,295.0,362.0,988.0,1585.0,2015.0,2172.0,2045.0,1582.0,805.0,115.0,832.0,1302.0,1568.0,1622.0,1435.0,1088.0,645.0,72.0,678.0,1632.0])
V2 = np.array([1958.0,908.0,2.0,735.0,1295.0,1652.0,1790.0,1658.0,1278.0,690.0,102.0,1035.0,1638.0,1750.0,1548.0,1512.0,1720.0,1818.0,1268.0,72.0,1110.0,1722.0,1738.0,1175.0,65.0])
V3 = np.array([1962.0,935.0,80.0,622.0,1182.0,1610.0,1848.0,1788.0,1415.0,740.0,185.0,1232.0,1860.0,1882.0,1520.0,1370.0,1538.0,1658.0,1170.0,45.0,1088.0,1685.0,1728.0,1212.0,98.0])
V4 = np.array([452.0,950.0,1212.0,1205.0,902.0,302.0,445.0,1160.0,1778.0,2138.0,2150.0,1860.0,1368.0,680.0,145.0,792.0,1188.0,1355.0,1422.0,1425.0,1272.0,860.0,208.0,640.0,1630.0])

#interpolation 25 points petite trajectoire réelle
data = np.array([
[0.00, 789, -707, 730, -768, 1963, 1759, 1818, 1913],
[0.31, 1272, -1097, 1159, -1222, 1705, 1420, 1530, 1618],
[0.62, 1701, -1421, 1527, -1618, 1486, 1143, 1287, 1377],
[0.94, 2087, -1692, 1848, -1968, 1304, 923, 1090, 1185],
[1.25, 2434, -1921, 2130, -2279, 1163, 767, 943, 1041],
[1.56, 2753, -2118, 2386, -2559, 1092, 687, 880, 964],
[1.87, 3075, -2317, 2651, -2837, 1068, 660, 872, 928],
[2.18, 3404, -2524, 2930, -3117, 1092, 682, 922, 930],
[2.50, 3755, -2750, 3240, -3408, 1168, 753, 1030, 969],
[2.81, 4169, -3028, 3630, -3735, 1325, 884, 1233, 1058],
[3.12, 4639, -3352, 4093, -4091, 1523, 1043, 1485, 1163],
[3.43, 5152, -3706, 4610, -4461, 1705, 1177, 1716, 1241],
[3.74, 5692, -4073, 5165, -4834, 1802, 1226, 1849, 1244],
[4.06, 6166, -4379, 5654, -5139, 1636, 1072, 1688, 1074],
[4.37, 6522, -4599, 6018, -5364, 1286, 804, 1318, 817],
[4.68, 6726, -4712, 6217, -5494, 752, 458, 769, 476],
[4.99, 6730, -4693, 6201, -5506, 31, 73, 70, 49],
[5.30, 6455, -4493, 5888, -5349, 693, 515, 797, 404],
[5.62, 6060, -4222, 5460, -5104, 1227, 851, 1339, 748],
[5.93, 5574, -3901, 4957, -4784, 1589, 1054, 1657, 1040],
[6.24, 5044, -3568, 4437, -4409, 1758, 1108, 1728, 1243],
[6.55, 4554, -3312, 4026, -4024, 1672, 921, 1467, 1278],
[6.87, 4117, -3135, 3720, -3659, 1500, 652, 1105, 1233],
[7.18, 3729, -3027, 3505, -3317, 1305, 379, 739, 1147],
[7.49, 3381, -2972, 3363, -2997, 1161, 189, 480, 1066],
[7.81, 3060, -2932, 3251, -2695, 1093, 144, 398, 1023],
[8.12, 2735, -2863, 3116, -2395, 1082, 206, 430, 1003],
[8.43, 2396, -2742, 2935, -2091, 1122, 375, 576, 1011],
[8.74, 2030, -2542, 2679, -1773, 1212, 655, 844, 1054],
[9.06, 1603, -2166, 2255, -1417, 1372, 1105, 1274, 1153],
[9.37, 1122, -1626, 1673, -1013, 1560, 1668, 1813, 1309],
[9.68, 586, -897, 914, -545, 1766, 2349, 2458, 1532],
[9.99, -6, 54, -54, 9, 1975, 3156, 3210, 1841],
[10.30, -24, 82, -82, 25, 1982, 3180, 3232, 1850]])


X1 = np.array([786.0,1434.0,1974.0,2439.0,2866.0,3293.0,3761.0,4313.0,4983.0,5705.0,6335.0,6725.0,6731.0,6353.0,5738.0,5033.0,4377.0,3837.0,3374.0,2946.0,2508.0,2022.0,1450.0,769.0,-24.0])
X2 = np.array([-705.0,-1228.0,-1618.0,-1924.0,-2188.0,-2452.0,-2754.0,-3126.0,-3591.0,-4082.0,-4488.0,-4719.0,-4693.0,-4420.0,-4005.0,-3561.0,-3220.0,-3045.0,-2971.0,-2919.0,-2803.0,-2538.0,-2031.0,-1190.0,82.0])
X3 = np.array([728.0,1302.0,1757.0,2134.0,2477.0,2832.0,3245.0,3767.0,4437.0,5178.0,5829.0,6223.0,6201.0,5772.0,5118.0,4426.0,3878.0,3550.0,3360.0,3212.0,3014.0,2674.0,2102.0,1211.0,-82.0])
X4 = np.array([-766.0,-1374.0,-1867.0,-2283.0,-2658.0,-3025.0,-3413.0,-3849.0,-4345.0,-4843.0,-5248.0,-5491.0,-5507.0,-5291.0,-4900.0,-4401.0,-3885.0,-3416.0,-2990.0,-2587.0,-2188.0,-1766.0,-1290.0,-715.0,25.0])

V1 = np.array([1965.0,1620.0,1350.0,1162.0,1068.0,1068.0,1170.0,1380.0,1675.0,1805.0,1575.0,975.0,15.0,945.0,1538.0,1762.0,1640.0,1350.0,1158.0,1070.0,1095.0,1215.0,1430.0,1702.0,1982.0])
V2 = np.array([1762.0,1308.0,975.0,765.0,660.0,660.0,755.0,930.0,1162.0,1228.0,1015.0,578.0,65.0,682.0,1038.0,1110.0,852.0,438.0,185.0,130.0,290.0,662.0,1268.0,2102.0,3180.0])
V3 = np.array([1820.0,1435.0,1138.0,942.0,858.0,888.0,1032.0,1305.0,1675.0,1852.0,1628.0,985.0,55.0,1072.0,1635.0,1730.0,1370.0,820.0,475.0,370.0,495.0,850.0,1430.0,2228.0,3232.0])
V4 = np.array([1915.0,1520.0,1232.0,1040.0,938.0,918.0,970.0,1090.0,1240.0,1245.0,1012.0,608.0,40.0,540.0,978.0,1248.0,1290.0,1172.0,1065.0,1008.0,998.0,1055.0,1190.0,1438.0,1850.0])

#interpolation 25 points petite trajectoire réelle
data = np.array([
[0.00, 1362, -3290, 3342, -950, 3397, 8205, 8335, 2371],
[0.31, 3083, -3726, 4065, -2499, 5168, 3158, 3911, 4478],
[0.63, 4864, -3176, 4047, -4341, 5872, 2468, 1859, 5883],
[0.94, 6533, -1902, 3458, -6211, 5674, 4055, 1799, 6324],
[1.25, 7957, -169, 2478, -7878, 4772, 5799, 3277, 5587],
[1.56, 8552, 1429, 1239, -8520, 2697, 5470, 3929, 3021],
[1.87, 8529, 2789, -149, -8395, 1576, 4756, 4524, 1952],
[2.18, 8026, 4044, -1731, -7628, 1549, 4187, 5199, 2364],
[2.49, 7178, 5349, -3565, -6334, 2807, 4354, 6107, 4281],
[2.81, 6133, 6767, -5562, -4577, 3324, 4638, 6531, 5478],
[3.12, 4750, 7676, -7026, -2669, 4352, 3486, 5369, 6280],
[3.43, 2894, 7860, -7648, -650, 5978, 2288, 3557, 6745],
[3.74, 374, 6998, -6977, 1424, 8313, 2852, 2273, 6902],
[4.05, -2444, 5465, -5027, 3529, 9154, 4552, 5435, 6996],
[4.36, -4897, 4136, -3046, 5451, 8527, 4639, 6637, 6588],
[4.67, -6875, 3026, -1194, 7083, 6846, 3794, 6310, 5624],
[4.99, -8228, 2130, 365, 8267, 4598, 3014, 5234, 4009],
[5.30, -8668, 923, 1837, 8708, 2241, 3773, 4996, 2102],
[5.61, -8439, -648, 3364, 8678, 1671, 4956, 5053, 1200],
[5.92, -7584, -2499, 4895, 8223, 2654, 6125, 5135, 1390],
[6.23, -6130, -4512, 6348, 7382, 4755, 6708, 4881, 2741],
[6.54, -4247, -6318, 7499, 6171, 5942, 6226, 4110, 3742],
[6.86, -2384, -7659, 8281, 4814, 6246, 4847, 2901, 4420],
[7.17, -719, -8383, 8601, 3391, 5732, 2847, 1671, 4787],
[7.48, 578, -8274, 8303, 1935, 4445, 535, 1046, 4871],
[7.79, 1548, -7468, 7502, 520, 3517, 2105, 2251, 4762],
[8.10, 2461, -6545, 6679, -825, 3065, 3023, 2756, 4537],
[8.42, 3303, -5610, 5910, -2045, 2840, 3136, 2593, 4125],
[8.73, 4005, -4761, 5260, -3039, 2387, 2863, 2207, 3385],
[9.04, 4151, -3887, 4456, -3467, 949, 2892, 2552, 1899],
[9.35, 3657, -2886, 3356, -3255, 1520, 3234, 3431, 1625],
[9.66, 2419, -1643, 1900, -2264, 3860, 4029, 4739, 3004],
[9.98, 167, 77, -59, -154, 7215, 5590, 6375, 6716],
[10.29, -5, 209, -209, 7, 7472, 5710, 6500, 7000]])


X1 = np.array([1357.0,3663.0,6054.0,7962.0,8756.0,8295.0,7162.0,5761.0,3649.0,294.0,-3484.0,-6483.0,-8285.0,-8821.0,-7999.0,-6051.0,-3495.0,-1065.0,675.0,1935.0,3119.0,4060.0,4192.0,2984.0,-5.0])
X2 = np.array([-3289.0,-3873.0,-2486.0,-164.0,1978.0,3632.0,5375.0,7271.0,8119.0,6971.0,4894.0,3286.0,2093.0,458.0,-1926.0,-4622.0,-7027.0,-8412.0,-8266.0,-7116.0,-5833.0,-4696.0,-3530.0,-2075.0,209.0])
X3 = np.array([3340.0,4309.0,3788.0,2475.0,814.0,-1151.0,-3601.0,-6272.0,-7849.0,-6956.0,-4295.0,-1646.0,430.0,2398.0,4481.0,6428.0,7946.0,8681.0,8281.0,7159.0,6081.0,5210.0,4123.0,2391.0,-209.0])
X4 = np.array([-946.0,-3021.0,-5650.0,-7884.0,-8740.0,-8037.0,-6310.0,-3951.0,-1272.0,1491.0,4303.0,6740.0,8317.0,8865.0,8463.0,7337.0,5685.0,3779.0,1828.0,-57.0,-1785.0,-3116.0,-3623.0,-2793.0,7.0])

V1 = np.array([3392.0,5765.0,5978.0,4770.0,1985.0,1152.0,2832.0,3502.0,5280.0,8388.0,9445.0,7498.0,4505.0,1340.0,2055.0,4870.0,6390.0,6075.0,4350.0,3150.0,2960.0,2352.0,330.0,3020.0,7472.0])
V2 = np.array([8222.0,1460.0,3468.0,5805.0,5355.0,4135.0,4358.0,4740.0,2120.0,2870.0,5192.0,4020.0,2982.0,4088.0,5960.0,6740.0,6012.0,3462.0,365.0,2875.0,3208.0,2842.0,2915.0,3638.0,5710.0])
V3 = np.array([8350.0,2422.0,1302.0,3282.0,4152.0,4912.0,6125.0,6678.0,3942.0,2232.0,6652.0,6622.0,5190.0,4920.0,5208.0,4868.0,3795.0,1838.0,1000.0,2805.0,2695.0,2178.0,2718.0,4330.0,6500.0])
V4 = np.array([2365.0,5188.0,6572.0,5585.0,2140.0,1758.0,4318.0,5898.0,6698.0,6908.0,7030.0,6092.0,3942.0,1370.0,1005.0,2815.0,4130.0,4765.0,4878.0,4712.0,4320.0,3328.0,1268.0,2075.0,7000.0])
